12-ch, HD video processor looks to autonomous car systems

February 03, 2016 //
By Graham Prophet

Renesas Electronics has developed a video processing circuit block for use in automotive computing SoCs that it expects to be applied autonomous vehicles of the future; the IP block achieves 70 msec-latency vehicle camera video processing and full-HD 12-channel video processing on 197 mW power.

Automotive computing SoCs for autonomous vehicles will, Renesas notes, be required to integrate the functionality of both in-vehicle infotainment systems and driving safety support systems, and to operate both in parallel. In particular, driving safety support systems must be able to process video data from vehicle cameras with low latency to notify the driver of appropriate information in a timely manner. One issue that developers of in-vehicle infotainment systems and driving safety support systems face is the need to process large amounts of video data and also to perform autonomous vehicle control functions, without delays and instability.

This video processing circuit block handles processing of vehicle camera video with low latency. It can perform video processing in real time on large volumes of video data with low power consumption and without imposing any additional load on the CPU and graphics processing unit (GPU), which are responsible for autonomous vehicle control. Renesas has manufactured prototypes of the new video processing circuit block using a 16 nm FinFET process, yielding the performance noted above.

Driving safety support systems are expected to perform cognitive processing based on video transferred from vehicle cameras, such as identifying obstacles, monitoring the status of the driver, and anticipating and avoiding hazards. With the appearance of devices such as the R-Car T2 vehicle camera network SoC from Renesas, it can be anticipated that video data transferred from vehicle cameras will be encoded to video streams, and driving safety support systems must decode the received video streams. In order to carry out cognitive processing correctly using images from wide-angle cameras, the video data must be processed to correct for distortion. This video processing will be required to be accomplished with low latency to enable the system to notify the driver of appropriate information in a timely manner.

On the other hand, in-vehicle infotainment systems are capable of interoperating with a variety of devices and services, including smartphones and cloud-based